diff --git a/.gitignore b/.gitignore
index 6c39e54b9..8afcd96f8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -36,6 +36,7 @@ pom.xml.versionsBackup
 pom.xml.next
 release.properties
 *dependency-reduced-pom.xml
+*/build/*
 
 # Specific for Nd4j
 *.md5
diff --git a/cavis-dnn/cavis-dnn-api/src/main/java/org/nd4j/linalg/dataset/DataSet.java b/cavis-dnn/cavis-dnn-api/src/main/java/org/nd4j/linalg/dataset/DataSet.java
index 222990cc5..d0c691cad 100644
--- a/cavis-dnn/cavis-dnn-api/src/main/java/org/nd4j/linalg/dataset/DataSet.java
+++ b/cavis-dnn/cavis-dnn-api/src/main/java/org/nd4j/linalg/dataset/DataSet.java
@@ -334,6 +334,7 @@ public class DataSet implements org.nd4j.linalg.dataset.api.DataSet {
     public void save(File to) {
         try (FileOutputStream fos = new FileOutputStream(to, false);
                         BufferedOutputStream bos = new BufferedOutputStream(fos)) {
+            to.mkdirs();
             save(bos);
         } catch (IOException e) {
             throw new RuntimeException(e);
diff --git a/cavis-dnn/cavis-dnn-core/src/test/java/org/deeplearning4j/datasets/iterator/DataSetIteratorTest.java b/cavis-dnn/cavis-dnn-core/src/test/java/org/deeplearning4j/datasets/iterator/DataSetIteratorTest.java
index cf3aff480..e33eebd6e 100644
--- a/cavis-dnn/cavis-dnn-core/src/test/java/org/deeplearning4j/datasets/iterator/DataSetIteratorTest.java
+++ b/cavis-dnn/cavis-dnn-core/src/test/java/org/deeplearning4j/datasets/iterator/DataSetIteratorTest.java
@@ -166,10 +166,10 @@ public class DataSetIteratorTest extends BaseDL4JTest {
         int seed = 123;
         int listenerFreq = 1;
 
-        LFWDataSetIterator lfw = new LFWDataSetIterator(batchSize, numSamples,
+        final LFWDataSetIterator lfw = new LFWDataSetIterator(batchSize, numSamples,
                         new int[] {numRows, numColumns, numChannels}, outputNum, false, true, 1.0, new Random(seed));
 
-        NeuralNetConfiguration.NeuralNetConfigurationBuilder builder = NeuralNetConfiguration.builder().seed(seed)
+        final var builder = NeuralNetConfiguration.builder().seed(seed)
                         .gradientNormalization(GradientNormalization.RenormalizeL2PerLayer)
                         .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
                         .layer(0, ConvolutionLayer.builder(5, 5).nIn(numChannels).nOut(6)
@@ -181,7 +181,7 @@ public class DataSetIteratorTest extends BaseDL4JTest {
                                         .build())
                         .inputType(InputType.convolutionalFlat(numRows, numColumns, numChannels));
 
-        MultiLayerNetwork model = new MultiLayerNetwork(builder.build());
+        final MultiLayerNetwork model = new MultiLayerNetwork(builder.build());
         model.init();
 
         model.addTrainingListeners(new ScoreIterationListener(listenerFreq));